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Drifting is an advanced driving technique where the wheeled robot's tire-ground interaction breaks the common non-holonomic pure rolling constraint. This allows high-maneuverability tasks like quick cornering, and steady-state drifting…

Robotics · Computer Science 2025-12-01 Feilong Jing , Yang Deng , Boyi Wang , Xudong Zheng , Yifan Sun , Zhang Chen , Bin Liang

We present a novel method for guaranteeing linear momentum in learned physics simulations. Unlike existing methods, we enforce conservation of momentum with a hard constraint, which we realize via antisymmetrical continuous convolutional…

Machine Learning · Computer Science 2022-11-03 Lukas Prantl , Benjamin Ummenhofer , Vladlen Koltun , Nils Thuerey

Ultrafast dynamical processes in photoexcited molecules can be observed with pump-probe measurements, in which information about the dynamics is obtained from the transient signal associated with the excited state. Background signals…

Atomic Physics · Physics 2018-06-11 M. Rumetshofer , P. Heim , B. Thaler , W. E. Ernst , M. Koch , W. von der Linden

We study electron pumping through a system of barriers, whose heights are deformed adiabatically. We derive a simple formula for the pumped charge $Q$ in terms of the total reflection and transmission amplitudes and phases. The pumped…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Argha Banerjee , Sourin Das , Sumathi Rao

Dynamic quantum dots are known to generate very accurate currents and can be used as a source of single electron wavepackets for use in quantum metrology, sensing or information processing. To realise their full technological potential, it…

Mesoscale and Nanoscale Physics · Physics 2024-10-14 Nathan Johnson , Gento Yamahata , Akira Fujiwara

A macroscopic fluid pump works according to the law of Newtonian mechanics and transfers a large number of molecules per cycle (of the order of 10^23). By contrast, a nano-scale charge pump can be thought as the ultimate miniaturization of…

Mesoscale and Nanoscale Physics · Physics 2011-11-24 F. Giazotto , P. Spathis , S. Roddaro , S. Biswas , F. Taddei , M. Governale , L. Sorba

In this paper, we propose an approach to learn stable dynamical systems evolving on Riemannian manifolds. The approach leverages a data-efficient procedure to learn a diffeomorphic transformation that maps simple stable dynamical systems…

Robotics · Computer Science 2023-09-27 Matteo Saveriano , Fares J. Abu-Dakka , Ville Kyrki

Testing for change points in sequences of covariance matrices is an important and equally challenging problem in statistical methodology with applications in various fields. Motivated by the observation that even in cases where the ratio…

Statistics Theory · Mathematics 2026-01-14 Nina Dörnemann , Holger Dette

We consider a single copy of a quantum particle moving in a potential and show that it is possible to monitor its complete wave function by only continuously measuring its position. While we assume that the potential is known, no…

Quantum Physics · Physics 2015-05-13 Thomas Konrad , Andreas Rothe , Francesco Petruccione , Lajos Diósi

Recent experiments on nanoscale conductors coupled to microwave cavities put in prospect transport investigations of electron-photon interplay in the deep quantum regime. Here we propose a pump-probe scheme to investigate the transient…

Mesoscale and Nanoscale Physics · Physics 2015-06-18 T. L. van den Berg , C. Bergenfeldt , P. Samuelsson

Quantum processes of inherent dynamical nature, such as quantum walks (QWs), defy a description in terms of an equilibrium statistical physics ensemble. Up to now, it has remained a key challenge to identify general principles behind the…

The dynamic capture of electrons in a semiconductor quantum dot (QD) by raising a potential barrier is a crucial stage in metrological quantized charge pumping. In this work, we use a quantum point contact (QPC) charge sensor to study…

Mesoscale and Nanoscale Physics · Physics 2018-09-27 S. P. Giblin , P. See , A. Petrie , T. J. B. M. Janssen , I. Farrer , J. P. Griffiths , G. A. C. Jones , D. A. Ritchie , M. Kataoka

As the method to completely characterize quantum dynamical processes, quantum process tomography (QPT) is vitally important for quantum information processing and quantum control, where the faithfulness of quantum devices plays an essential…

Quantum Physics · Physics 2013-09-24 Yu-Xiang Zhang , Shengjun Wu , Zeng-Bing Chen

We show that the energy required by a turbulent flow to displace a given amount of fluid through a straight duct in a given time interval can be reduced by modulating in time the pumping power. The control strategy is hybrid: it is passive,…

Fluid Dynamics · Physics 2024-05-15 Giulio Foggi Rota , Alessandro Monti , Marco E. Rosti , Maurizio Quadrio

In this work we study drawdowns and drawups of general diffusion processes. The drawdown process is defined as the current drop of the process from its running maximum, while the drawup process is defined as the current increase over its…

Probability · Mathematics 2009-11-10 Hongzhong Zhang , Olympia Hadjiliadis

Experimental investigations of the exit dynamics of a horizontal cylindrical object were performed in water and silicone oil (50 cSt). The fully immersed cylinder was initially at rest in a still fluid tank before being pushed (or pulled…

We describe a generalized algorithm for evaluating the steady-state solution of the density matrix equation of motion, for the pump-probe scheme, when two fields oscillating at different frequencies couple the same set of atomic transitions…

Quantum Physics · Physics 2024-01-31 Zifan Zhou , Yael Sternfeld , Jacob Scheuer , Selim M. Shahriar

Quantum dots must be tuned precisely to provide a suitable basis for quantum computation. A scalable platform for quantum computing can only be achieved by fully automating the tuning process. One crucial step is to trap the appropriate…

Mesoscale and Nanoscale Physics · Physics 2025-08-12 Fabian Hader , Sarah Fleitmann , Jan Vogelbruch , Lotte Geck , Stefan van Waasen

The breakthrough of deep Q-Learning on different types of environments revolutionized the algorithmic design of Reinforcement Learning to introduce more stable and robust algorithms, to that end many extensions to deep Q-Learning algorithm…

Machine Learning · Computer Science 2024-04-16 Mohammed Sabry , Amr M. A. Khalifa

The transition between the two phases of 4D Euclidean Dynamical Triangulation [1] was long believed to be of second order until in 1996 first order behavior was found for sufficiently large systems [5,9]. However, one may wonder if this…

High Energy Physics - Lattice · Physics 2021-11-18 Tobias Rindlisbacher , Philippe de Forcrand